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Data Modeling Master Class Training Manual Steve Hobermans Best Practices Approach to Understanding at Meripustak

Data Modeling Master Class Training Manual Steve Hobermans Best Practices Approach to Understanding by Steve Hoberman , Technics Publications

Books from same Author: Steve Hoberman

Books from same Publisher: Technics Publications

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  • General Information  
    Author(s)Steve Hoberman
    PublisherTechnics Publications
    ISBN9781634621946
    Pages346
    BindingPaperback
    LanguageEnglish
    Publish YearJuly 2017

    Description

    Technics Publications Data Modeling Master Class Training Manual Steve Hobermans Best Practices Approach to Understanding by Steve Hoberman

    This is the seventh edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com._x000D_The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard(R). You will know not just how to build a data model, but how to build a data model well. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects._x000D_Top 10 Objectives_x000D_1. Explain data modeling components and identify them on your projects by following a question-driven approach_x000D_2. Demonstrate reading a data model of any size and complexity with the same confidence as reading a book_x000D_3. Validate any data model with key "settings" (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard(R)_x000D_4. Apply requirements elicitation techniques including interviewing, artifact analysis, prototyping, and job shadowing_x000D_5. Build relational and dimensional conceptual and logical data models, and know the tradeoffs on the physical side for both RDBMS and NoSQL solutions_x000D_6. Practice finding structural soundness issues and standards violations_x000D_7. Recognize when to use abstraction and where patterns and industry data models can give us a great head start_x000D_8. Use a series of templates for capturing and validating requirements, and for data profiling_x000D_9. Evaluate definitions for clarity, completeness, and correctness_x000D_10. Leverage the Data Vault and enterprise data model for a successful enterprise architecture._x000D_ Table of contents : - _x000D_ Business Processes in the Sales Area Using SAP SD - Using CATT for the Implementation - How to automate Tests and optimize R/3 Business Processes - The Pricing Technology in SD: Difficulties unravelled - R/3 Module SD and Sales on the Internet - The new Implementation Process Using ASAP - How to Realize Supply Chain Management_x000D_



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